Vom Input zum Output

Infolge der durch die internationalen Schulvergleichstests eingeleiteten empirischen Wende in der Erziehungswissenschaft hat sich die Aufmerksamkeit vom Input schulischen Lehrens und Lernens zunehmend auf die Ergebnisse (Output) bzw. Wirkungen (Outcomes) verlagert. Die Kernfrage lautet nun: Was kommt am Ende in der Schule bzw. im Unterricht eigentlich heraus? Grundlegende Voraussetzung ergebnisorienterter Steuerung schulischen Unterrichts ist die Formulierung von Bildungsstandards. Wie Bildungsstandards mit Kompetenzmodellen und konkreten Aufgabenstellungen im Unterricht des Faches "Politik & Wirtschaft" verknüpft werden können, wird in diesem Beitrag einer genaueren Analyse unterzogen. Vor dem Hintergrund bildungstheoretischer Vorstellungen im Anschluss an Immanuel Kant kommen dabei das Literacy-Konzept der Pisa-Studie sowie die "Dokumentarische Methode" nach Karl Mannheim zur Anwendung.

Comparing Input- and Output-Oriented Measures of Technical Efficiency to Determine Local Returns to Scale in DEA Models

This paper shows how one can infer the nature of local returns to scale at the input- or output-oriented efficient projection of a technically inefficient input-output bundle, when the input- and output-oriented measures of efficiency differ.

Analysis of output properties of the Peroxiredoxin/Thioredoxin/Thioredoxin reductase system

Dissertação de mestrado em Bioinformática

O Modelo unput-output no planeamento de longo prazo

Doutoramento em Economia.

The Distribution Dynamics of Output Multipliers in Scotland 1998–2007

In an input-output context the impact of any particular industrial sector is commonly measured in terms of the output multiplier for that industry. Although such measures are routinely calculated and often used to guide regional industrial policy the behaviour of such measures over time is an area that has attracted little academic study. The output multipliers derived from any one table will have a distribution; for some industries the multiplier will be relatively high, for some it will be relatively low. The recentpublication of consistent input-output tables for the Scottish economy makes it possible to examine trends in this mdistribution over the ten year period 1998-2007. This is done by comparing the means and other summary measures of the distributions, the histograms and the cumulative densities. The results indicate a tendency for the multipliers to increase over the period. A Markov chain modelling approach suggests that this drift is a slow but long term phenomenon which appears not to tend to an equilibrium state. The prime reason for the increase in the output multipliers is traced to a decline in the relative importance of imported (both from the rest of the UK and the rest of the world) intermediate inputs used by Scottish industries. This suggests that models calibrated on the set of tables might have to be interpreted with caution.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Input diffusion and the evolution of production networks

What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

A slide scanner input for paramatrix,

"Supported in part by the Office of Naval Research. Contract no.N00014-67-A-0305-0007."

Subcellular localization determines MAP kinase signal output

The Raf-MEK-ERK MAP kinase cascade transmits signals from activated receptors into the cell to regulate proliferation and differentiation. The cascade is controlled by the Ras GTPase, which recruits Raf from the cytosol to the plasma membrane for activation. In turn, MEK, ERK, and scaffold proteins translocate to the plasma membrane for activation. Here, we examine the input-output properties of the Raf-MEK-ERK MAP kinase module in mammalian cells activated in different cellular contexts. We show that the MAP kinase module operates as a molecular switch in vivo but that the input sensitivity of the module is determined by subcellular location. Signal output from the module is sensitive to low-level input only when it is activated at the plasma membrane. This is because the threshold for activation is low at the plasma membrane, whereas the threshold for activation is high in the cytosol. Thus, the circuit configuration of the module at the plasma membrane generates maximal outputs from low-level analog inputs, allowing cells to process and respond appropriately to physiological stimuli. These results reveal the engineering logic behind the recruitment of elements of the module from the cytosol to the membrane for activation.

A Family of Autoconnected Transformers for 12-and 18-Pulse Converters-Generalization for Delta and Wye Topologies

Multipulse rectifier topologies based on autoconnections are increasingly applied as interface stages between mains and power electronics converters. These topologies are attractive and cost-effective solutions for meeting the requirements of low total harmonic distortion of line current and high power factor. Furthermore, as only a small fraction of the total power required by the load is processed in the magnetic core, the overall resulting volume and weight are reduced. This paper proposes a mathematical analysis based on phasor diagrams that results in a single and general expression capable of unifying all delta and wye step-up or step-down autotransformer connections for 12-and 18-pulse ac-dc converters. The expression obtained allows the choice of a wide range of input/output voltage ratio for step-up or step-down autotransformer, and this general expression is also presented in a graphical form for each converter. Moreover, it simplifies the procedure for determining turn ratios and polarities for all windings of the autotransformer. A routine for easy and fast calculations is developed and validated by a design example. Finally, experimental results are presented along with comments on a 6-kW 220-V line voltage, 400-V rectified voltage, and 18-pulse delta-autoconnected prototype.

Infinite horizon MPC with non-minimal state space feedback

In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.

Biogeochemical cycles of nutrients in tropical Eucalyptus plantations Main features shown by intensive monitoring in Congo and Brazil

The sustainability of fast-growing tropical Eucalyptus plantations is of concern in a context of rising fertilizer costs, since large amounts of nutrients are removed with biomass every 6-7 years from highly weathered soils. A better understanding of the dynamics of tree requirements is required to match fertilization regimes to the availability of each nutrient in the soil. The nutrition of Eucalyptus plantations has been intensively investigated and many studies have focused on specific fluxes in the biogeochemical cycles of nutrients. However, studies dealing with complete cycles are scarce for the Tropics. The objective of this paper was to compare these cycles for Eucalyptus plantations in Congo and Brazil, with contrasting climates, soil properties, and management practices. The main features were similar in the two situations. Most nutrient fluxes were driven by crown establishment the two first years after planting and total biomass production thereafter. These forests were characterized by huge nutrient requirements: 155, 10, 52, 55 and 23 kg ha(-1) of N, P, K, Ca and Mg the first year after planting at the Brazilian study site, respectively. High growth rates the first months after planting were essential to take advantage of the large amounts of nutrients released into the soil solutions by organic matter mineralization after harvesting. This study highlighted the predominant role of biological and biochemical cycles over the geochemical cycle of nutrients in tropical Eucalyptus plantations and indicated the prime importance of carefully managing organic matter in these soils. Limited nutrient losses through deep drainage after clear-cutting in the sandy soils of the two study sites showed the remarkable efficiency of Eucalyptus trees in keeping limited nutrient pools within the ecosystem, even after major disturbances. Nutrient input-output budgets suggested that Eucalyptus plantations take advantage of soil fertility inherited from previous land uses and that long-term sustainability will require an increase in the inputs of certain nutrients. (C) 2009 Elsevier B.V. All rights reserved.

STRUCTURAL INTERDEPENDENCE AMONG COLOMBIAN DEPARTMENTS

This paper analyzes structural interdependence among Colombian departments. The results show that Bogota has a large influence on the other regional economies through the power of its purchases. Additionally, a center-periphery pattern emerges in the spatial concentration of the effects of the hypothetical extraction of any territory. From a policy point of view, the main findings reaffirm the role played by Bogota in the recent polarization process observed in the regional economies in Colombia. Any policy action oriented to reduce these regional disparities should take into account that, given the structural interdependence among Colombian departments, the effects of new investment in the lagged regions would flow through Bogota and the major regional economies.

Analysis of acousto-ultrasonic characteristics for contact-type transducers coupled to composite laminated plates

The acousto-ultrasonic (AU) input-output characteristics for contact-type transmitting and receiving transducers coupled to composite laminated plates are considered in this paper. Combining a multiple integral transform method, an ordinary discrete layer theory for the laminates and some simplifying assumptions for the electro-mechanical transduction behaviour of the transducers, an analytical solution is developed which can deal with all the wave processes involved in the AU measurement system, i.e, wave generation, wave propagation and wave reception. The spectral response of the normal contact pressure sensed by the receiving transducer due to an arbitrary input pulse excited by the transmitting transducer is obtained. To validate the new analytical-numerical spectral technique in the low-frequency regime, the results are compared with Mindlin plate theory solutions. Based on the analytical results, numerical calculations are carried out to investigate the influence of various external parameters such as frequency content of the input pulse, transmitter/receiver spacing and transducer aperture on the output of the measurement system. The results show that the presented analytical-numerical procedure is an effective tool for understanding the input-output characteristics of the AU technique for laminated plates. (C) 2001 Elsevier Science Ltd. All rights reserved.